ENTERPRISE RISK MANAGEMENT AT QATAR'S CONSTRUCTION INDUSTRY

Lately, enterprise risk management (ERM) is an emerging topic, which has attracted the worldwide attention. All organizations around the world recognize the importance of risk management regardless of their size or industry as it has been a response to the volatile environment. The Government of Qatar has recognized the importance of risk management and some of the ministries have applied risk management principles in their organizations. Because of the multitude in their operations, construction firms are prime candidates for ERM adoption. Although there is an increased number of studies on risk management around the world, limited studies have strived to provide an understanding of the implementation of Enterprise Risk Management (ERM) in the construction industry. This research investigates and provides an understanding of ERM implementation in the Qatari construction industry. This research tries to investigate the existing level of ERM in the Qatari construction industry. In addition, the research investigates the criteria that affect the ERM implementation and the factors that drive or hinder the ERM implementation in Qatar. By using a survey as the main data collection method, almost 80 construction companies have responded. The results reported a medium-level overall the ERM maturity in these companies. In addition, a total of 16 important maturity criteria and 64 applicable ERM best practices were identified and included in the survey questionnaire. The research found that 14 drivers and 32 hindrances had significantly positive and negative influence on ERM implementation in the construction companies in Qatar. The research has reviewed the literature and adapted the proposed ERM framework by Zhao proposes in his book on ERM in International construction operations. Since few studies have discussed the ERM implementation in construction firms in the Gulf region, this study is a pioneering contribution to the current literature of the ERM in Qatar’s construction Industry

Prevalence and management of diabetic neuropathy in secondary care in Qatar

Aims Diabetic neuropathy (DN) is a “Cinderella” complication, particularly in the Middle East. A high prevalence of undiagnosed DN and those at risk of diabetic foot ulceration (DFU) is a major concern. We have determined the prevalence of DN and its risk factors, DFU and those at risk of (DFU) in patients with T2DM in secondary care in Qatar. Materials and methods Adults with T2DM were randomly selected from the two National Diabetes Centers in Qatar. DN was defined by the presence of neuropathic symptoms and a vibration perception threshold (VPT) ≥ 15 V. Participants with a VPT≥25 V were categorized as high risk for DFU. Painful DN was defined by a DN4 score ≥ 4. Logistic regression analysis was used to identify predictors of DN. Results In 1082 adults with T2DM (age 54 ± 11 years, duration of diabetes 10.0 ± 7.7 years, 60.6% males) the prevalence of DN was 23.0% (95% CI: 20.5%‐25.5%), of whom 33.7% (95% CI: 27.9%‐39.6%) were at high risk of DFU and 6.3% had DFU. 82.0% of the patients with DN were previously undiagnosed. The prevalence of DN increased with age and duration of diabetes and was associated with poor glycemic control (HbA1c ≥ 9%) AOR = 2.1 (95%CI: 1.3‐3.2), hyperlipidemia AOR = 2.7 (95%CI: 1.5‐5.0) and hypertension AOR = 2.0 (95%CI: 1.2‐3.4). Conclusions Despite, DN affecting 23% of adults with T2DM, 82% had not been previously diagnosed with 1/3 at high risk for DFU. This argues for annual screening and identification of patients with DN. Furthermore, we identify hyperglycemia, hyperlipidemia and hypertension as predictors of DN

Prevalence and risk factors for painful diabetic neuropathy in secondary health care in Qatar.

AIMS/INTRODUCTION:Painful diabetic peripheral neuropathy (PDPN) has a significant impact on the patient's quality of life. The prevalence of PDPN in the Middle East and North Africa (MENA) region has been reported to be almost double that of populations in the UK. We sought to determine the prevalence of PDPN and its associated factors in T2DM patients attending secondary care in Qatar. MATERIALS AND METHODS:This is a cross-sectional study of 1095 participants with T2DM attending Qatar's two national diabetes centers. PDPN and impaired vibration perception on the pulp of the large toes were assessed using the DN4 questionnaire with a cut-off ≥4 and the Neurothesiometer with a cut-off ≥15V, respectively. RESULTS:The prevalence of PDPN was 34.5% (95% CI: 31.7%-37.3%), but 80% of these patients had not previously been diagnosed or treated for this condition. Arabs had a higher prevalence of PDPN compared to South Asians (P<0.05). PDPN was associated with impaired vibration perception AOR=4.42 (95%CI: 2.92-6.70), smoking AOR=2.43 (95%CI: 1.43-4.15), obesity AOR=1.74 (95%CI: 1.13-2.66), being female AOR=1.65 (95%CI: 1.03-2.64) and duration of diabetes AOR=1.08 (95%CI: 1.05-1.11). Age, poor glycemic control, hypertension, physical activity and proteinuria showed no association with PDPN. CONCLUSIONS:PDPN occurs in 1/3 of T2DM patients attending secondary care in Qatar, but the majority have not been diagnosed. Arabs are at higher risk for PDPN. Impaired vibration perception, obesity and smoking are associated with PDPN in Qatar. This article is protected by copyright. All rights reserved

AN OPTIMIZATION FRAMEWORK FOR ELECTRIC VEHICLES CHARGING STATIONS ALLOCATION USING DEMAND BASED ON CITY TRAFFIC COUNT

Selecting good locations for the placement of Electric Vehicle (EV) public charging stations is important for the uptake of EVs. As EVs are considered to have lower green gas emissions to internal combustion engines, the uptake of EVs is considered better for the environment. Many factors are involved in the location-allocation problem for EV public charging stations, such as understanding demand, needs assessment, identifying possible locations, and selecting a facility location optimization model. This study provides a framework to improve demand identification and estimation accuracy and reliability by using traffic data and VISUM traffic simulation software. The case study of Doha is presented by applying three facility location optimization models. The set covering model results provide well-distributed stations, while the maximum coverage model locates stations in a concentrated area